Magazine Luiza, one of the largest retail chains in Brazil, developed an in-house product recommendation system, built on top of a large knowledge Graph. AWS resources like Amazon EC2, Amazon SQS, Amazon ElastiCache and others made it possible for them to scale from a very small dataset to a huge Cassandra cluster. By improving their big data processing algorithms on their in-house solution built on AWS, they improved their conversion rates on revenue by more than 25 percent compared to market solutions they had used in the past.
아마존닷컴처럼 Amazon Forecast로 시계열 예측하기 - 강지양 솔루션즈 아키텍트, AWS / 강태욱 매니저, GSSHOP :: A...Amazon Web Services Korea
아마존닷컴처럼 Amazon Forecast로 시계열 예측하기
강지양 솔루션즈 아키텍트, AWS
강태욱 매니저, GSSHOP
Amazon Forecast는 머신러닝을 통해 높은 정확도의 시계열 예측을 하는 서비스입니다. Amazon Forecast는 Amazon.com이 사용하는 기술을 그대로 사용하며 머신러닝 경험이 없어도 데이터만 있다면 바로 시작할 수 있습니다. 이 세션에서는 직접 서버를 구축하거나 머신러닝 모델을 개발, 학습, 배포할 필요없이 리테일, 물류, 재무관리에 적용할 수 있는 Amazon Forecast를 실제 사례와 함께 살펴봅니다.
O caminho para a nuvem tem muitas opções e diferentes passos. O intuito desse webinar é fornecer uma breve visão sobre a adoção da nuvem e dar subsidios para construção do seu roteiro de migração. Vamos falar sobre como construir seu roadmap de migração, entender diferentes padrões, métodos e sobre as possibilidades que a AWS tem alavancado com sucesso centenas de clientes em todo o mundo. Saiba quais os desafios que os clientes enfrentam ao planejar as migrações para cloud, e como eles superá-los para minimizar riscos e acelerar a adoção.
아마존닷컴처럼 Amazon Forecast로 시계열 예측하기 - 강지양 솔루션즈 아키텍트, AWS / 강태욱 매니저, GSSHOP :: A...Amazon Web Services Korea
아마존닷컴처럼 Amazon Forecast로 시계열 예측하기
강지양 솔루션즈 아키텍트, AWS
강태욱 매니저, GSSHOP
Amazon Forecast는 머신러닝을 통해 높은 정확도의 시계열 예측을 하는 서비스입니다. Amazon Forecast는 Amazon.com이 사용하는 기술을 그대로 사용하며 머신러닝 경험이 없어도 데이터만 있다면 바로 시작할 수 있습니다. 이 세션에서는 직접 서버를 구축하거나 머신러닝 모델을 개발, 학습, 배포할 필요없이 리테일, 물류, 재무관리에 적용할 수 있는 Amazon Forecast를 실제 사례와 함께 살펴봅니다.
O caminho para a nuvem tem muitas opções e diferentes passos. O intuito desse webinar é fornecer uma breve visão sobre a adoção da nuvem e dar subsidios para construção do seu roteiro de migração. Vamos falar sobre como construir seu roadmap de migração, entender diferentes padrões, métodos e sobre as possibilidades que a AWS tem alavancado com sucesso centenas de clientes em todo o mundo. Saiba quais os desafios que os clientes enfrentam ao planejar as migrações para cloud, e como eles superá-los para minimizar riscos e acelerar a adoção.
Landing Zones Creating a Foundation - AWS Summit Sydney 2018Amazon Web Services
Landing Zones: Creating a Foundation for Your AWS Migrations
When migrating lots of applications to the cloud, it's important to architect cloud environments that are efficient, secure and compliant. AWS Landing Zones are a prescriptive set of instructions for deploying an AWS-recommended foundation of interrelated AWS accounts, networks, and core services for your initial AWS application environments. This session will review the benefits and best practices.
Ali Juzer, Cloud Architect, Professional Services, Amazon Web Services
Abstract: Data preparation and modelling are the activities that take most of the time in a typical data scientist workday. In this session we’ll see how AWS services for Analytics and data management can be effectively used and integrated in AI/ML pipelines. We’ll focus on AWS Glue, AWS Glue DataBrew and AWS Data Wrangler with a bit of theory and hands-on demos.
Bio:
Francesco Marelli is a senior solutions architect at Amazon Web Services. He has lived and worked in UK, italy, Switzerland and other countries in EMEA. He is specialized in the design and implementation of Analytics, Data Management and Big Data systems. Francesco also has a strong experience in systems integration and design and implementation of applications.
Topics: machine learning pipelines, AWS, cloud.
Sometimes you just need to spin up a virtual server, install your LAMP stack or web app, and go. No complex configurations - just a few clicks and a simple, low price.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
slide internet das coisas apresentação
A Internet das Coisas (do inglês Internet of Things (IoT)) emergiu dos avanços de
várias áreas como sistemas embarcados, microeletrônica, comunicação e sensoriamento.
De fato, a IoT tem recebido bastante atenção tanto da academia quanto da indústria, devido ao seu potencial de uso nas mais diversas áreas das atividades humanas. Este capítulo
aborda a Internet das Coisas através de uma perspectiva teórica e prática. O conteúdo aqui
abordado explora a estrutura, organização, desafios e aplicações da IoT. Nesta seção, serão
conceituadas a IoT e os objetos inteligentes. Além disso, são apresentadas a perspectiva
histórica da Internet das Coisas e as motivações que levam aos interesses, expectativas e
pesquisas na área. Logo em seguida, são introduzidos os blocos básicos de construção
da IoT. Para iniciar a discussão, será levantada a seguinte questão: o que é a Internet das
Coisas?
A Internet das Coisas, em poucas palavras, nada mais é que uma extensão da
Internet atual, que proporciona aos objetos do dia-a-dia (quaisquer que sejam), mas com
capacidade computacional e de comunicação, se conectarem à Internet. A conexão com a
rede mundial de computadores viabilizará, primeiro, controlar remotamente os objetos e,
segundo, permitir que os próprios objetos sejam acessados como provedores de serviços.
Estas novas habilidades, dos objetos comuns, geram um grande número de oportunidades
tanto no âmbito acadêmico quanto no industrial. Todavia, estas possibilidades apresentam
riscos e acarretam amplos desafios técnicos e sociais.
Build a Recommendation Engine using Amazon Machine Learning in Real-timeAmazon Web Services
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. In this session, we will introduce how to use Amazon Machine Learning to create a data model, and use it to generate the real-time prediction for your application.
Amazon Machine Learning Case Study: Predicting Customer ChurnAmazon Web Services
We do a deeper dive into Amazon Machine Learning, using a specific business problem as an example – predicting if the customer is about to leave your service, also known as customer churn. We examine several practical aspects of building and using a model, including the use of the recipe language for training data manipulation and modeling the costs of false positive/negative errors.
Landing Zones Creating a Foundation - AWS Summit Sydney 2018Amazon Web Services
Landing Zones: Creating a Foundation for Your AWS Migrations
When migrating lots of applications to the cloud, it's important to architect cloud environments that are efficient, secure and compliant. AWS Landing Zones are a prescriptive set of instructions for deploying an AWS-recommended foundation of interrelated AWS accounts, networks, and core services for your initial AWS application environments. This session will review the benefits and best practices.
Ali Juzer, Cloud Architect, Professional Services, Amazon Web Services
Abstract: Data preparation and modelling are the activities that take most of the time in a typical data scientist workday. In this session we’ll see how AWS services for Analytics and data management can be effectively used and integrated in AI/ML pipelines. We’ll focus on AWS Glue, AWS Glue DataBrew and AWS Data Wrangler with a bit of theory and hands-on demos.
Bio:
Francesco Marelli is a senior solutions architect at Amazon Web Services. He has lived and worked in UK, italy, Switzerland and other countries in EMEA. He is specialized in the design and implementation of Analytics, Data Management and Big Data systems. Francesco also has a strong experience in systems integration and design and implementation of applications.
Topics: machine learning pipelines, AWS, cloud.
Sometimes you just need to spin up a virtual server, install your LAMP stack or web app, and go. No complex configurations - just a few clicks and a simple, low price.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
slide internet das coisas apresentação
A Internet das Coisas (do inglês Internet of Things (IoT)) emergiu dos avanços de
várias áreas como sistemas embarcados, microeletrônica, comunicação e sensoriamento.
De fato, a IoT tem recebido bastante atenção tanto da academia quanto da indústria, devido ao seu potencial de uso nas mais diversas áreas das atividades humanas. Este capítulo
aborda a Internet das Coisas através de uma perspectiva teórica e prática. O conteúdo aqui
abordado explora a estrutura, organização, desafios e aplicações da IoT. Nesta seção, serão
conceituadas a IoT e os objetos inteligentes. Além disso, são apresentadas a perspectiva
histórica da Internet das Coisas e as motivações que levam aos interesses, expectativas e
pesquisas na área. Logo em seguida, são introduzidos os blocos básicos de construção
da IoT. Para iniciar a discussão, será levantada a seguinte questão: o que é a Internet das
Coisas?
A Internet das Coisas, em poucas palavras, nada mais é que uma extensão da
Internet atual, que proporciona aos objetos do dia-a-dia (quaisquer que sejam), mas com
capacidade computacional e de comunicação, se conectarem à Internet. A conexão com a
rede mundial de computadores viabilizará, primeiro, controlar remotamente os objetos e,
segundo, permitir que os próprios objetos sejam acessados como provedores de serviços.
Estas novas habilidades, dos objetos comuns, geram um grande número de oportunidades
tanto no âmbito acadêmico quanto no industrial. Todavia, estas possibilidades apresentam
riscos e acarretam amplos desafios técnicos e sociais.
Build a Recommendation Engine using Amazon Machine Learning in Real-timeAmazon Web Services
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. In this session, we will introduce how to use Amazon Machine Learning to create a data model, and use it to generate the real-time prediction for your application.
Amazon Machine Learning Case Study: Predicting Customer ChurnAmazon Web Services
We do a deeper dive into Amazon Machine Learning, using a specific business problem as an example – predicting if the customer is about to leave your service, also known as customer churn. We examine several practical aspects of building and using a model, including the use of the recipe language for training data manipulation and modeling the costs of false positive/negative errors.
Amazon Machine Learning: Empowering Developers to Build Smart ApplicationsAmazon Web Services
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning’s powerful algorithms create machine learning (ML) models by finding patterns in your existing data. Then, the service uses these models to process new data and generate predictions for your application. Amazon Machine Learning can ingest data from Amazon S3, Amazon Redshift or Amazon RDS. In this session, we will demonstrate how Amazon Machine Learning can be used to build an ML model, deploy it to production, and query this model from within a smart application.
Building a Real-Time Geospatial-Aware Recommendation EngineAmazon Web Services
Recommendation engines help your prospects and customers find the most relevant offers and content. In this presentation, you will learn how to use AWS building blocks to build your own location-aware recommendation engine. You’ll see how to store real-time events using Amazon Kinesis and Amazon DynamoDB. See how to easily move data into Amazon Redshift using Kinesis Firehose. As your site or app rises in popularity, you’ll need to track a wider variety of events and scale to handle traffic and usage spikes. Learn architectural patterns for processing large datasets and high-request volume applications.
AWS ML and SparkML on EMR to Build Recommendation Engine Amazon Web Services
Machine Learning
A managed supervised learning environment to build different models, including Binary Classification / Multi-class classification / Regression ML. The demos will show a dataset of banking customers with demographics, predicting the likelihood of whether they are going to default using binary classification. Second one will be predicting a UK bike rental shop traffic using linear regression, and third one for predicting a rainforest soil type using multi-class classification.
Benefits: Managed and on-demand environment for supervised learning algorithm, available as batch processing or real-time API.
Spark ML Cluster
Running spark on AWS managed cluster, storing data on HDFS / S3 persistent storage, modules include MLib and Zeppelin (Web Notebook), to build a movie recommendation engine based on “Collaborative Filtering”. The dataset contains 10M ratings provided by grouplens from MovieLens website.
Benefits: Fully managed clusters, with HA, Scalability, Elasticity and Spot instance pricing
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure. More information: https://aws.amazon.com/machine-learning/
Simon Ellis from RPI presented “Aleph, A Cognitive Game-playing System for Tabletop Games”at the Cognitive Systems Institute Group Speaker Series call on November 12, 2015.
#Espc15: Build a knowledge social network with o365, yammer and office graphNicolas Georgeault
These slides are more about the concept of Corporate BigData and how Knowledge mostly contained out of documents can be stored and used to capitalize about the real value of a company: The Know-How
Scaling a Mobile Web App to 100 Million Clients and Beyond (MBL302) | AWS re:...Amazon Web Services
Mobile apps have different service requirements from their desktop and web-based analogs. Bandwidth, client processing, and other considerations can impose significant extra demands on a scalable service. This session is a technical discussion of the challenges Flipboard met while scaling a data-intensive mobile app from 0 to 100 million clients and how they are working on scaling 10x using AWS. At each major step, Flipboard has encountered many challenges. Learn about how they handled those challenges and the evolution of their systems architecture, design choices, and software selection.
How Trend Micro Build their Enterprise Security Offering on AWS (SEC307) | AW...Amazon Web Services
"In this session, learn how Trend Micro built Deep Security as a service on AWS. This service offers enterprise-grade security controls for AWS deployments in the form of intrusion detection and prevention, anti-malware, a firewall, web reputation, and integrity monitoring.
With over 400 internal requirements set by their in-house Information Security and IT Operations teams, the Service team was challenged with building the case to deploy Deep Security as a service on AWS instead of in-house. This session walks through the reasons why the team chose AWS, the design decisions they made, and how they were able to meet or exceed their in-house requirements while deploying on AWS."
Netflix: Amazon S3 & Amazon Elastic MapReduce to Monitor at Gigascale (BDT302...Amazon Web Services
How does Netflix stay on top of the operations of its Internet service with millions of users and billions of metrics? With Atlas, its own massively distributed, large-scale monitoring system. Come learn how Netflix built Atlas with multiple processing pipelines using Amazon S3 and Amazon EMR to provide low-latency access to billions of metrics while supporting query-time aggregation along multiple dimensions.
Diving Into the New AWS SDK for Ruby (TLS305) | AWS re:Invent 2013Amazon Web Services
Ruby developers: attend this session and learn about the next major version of the AWS SDK for Ruby, the aws-core gem. We dive deep into the SDK, covering topics such as waiters, request enumeration and pagination, resource modeling, version locking, and more. Learn how to take advantage of these features as we construct a sample Ruby application using the AWS SDK.
[Nuxeo World 2013] DID YOU SAY DAM? DIGITAL ASSET MANAGEMENT WITH THE NUXEO P...Nuxeo
Digital assets are content, just like any other document, and we know how to handle content. However, digital assets do have specific constraints that require specific answers. This session will give a demonstration of the new version of Nuxeo DAM, with an overview of both out-of-the-box features and configuration and customization possibilities with Nuxeo Studio.
Running Lean and Mean: Designing Cost-efficient Architectures on AWS (ARC313)...Amazon Web Services
Whether you're a startup getting to profitability or an enterprise optimizing spend, it pays to run cost-efficient architectures on AWS. Dive deep into techniques used by successful customers to reduce waste and fine-tune their AWS spending, often with improved performance and a better end-customer experience. Some techniques covered in this session: Learn how to make the most of Auto Scaling, develop an effective Spot Instance strategy, and optimize for your daily traffic cycles. Learn techniques to tier storage, offload your static content to Amazon S3 and Amazon CloudFront, reduce your database loads with edge caching, spawn part-time databases, pool resources across accounts, and even teach your dev/test instances to sleep. Showcasing easily-applicable methods, this session could be your best invested hour all day.
Running Lean and Mean: Designing Cost-efficient Architectures on AWS (ARC313)...Amazon Web Services
Whether you're a startup getting to profitability or an enterprise optimizing spend, it pays to run cost-efficient architectures on AWS. Dive deep into techniques used by successful customers to reduce waste and fine-tune their AWS spending, often with improved performance and a better end-customer experience. Some techniques covered in this session: Learn how to make the most of Auto Scaling, develop an effective Spot Instance strategy, and optimize for your daily traffic cycles. Learn techniques to tier storage, offload your static content to Amazon S3 and Amazon CloudFront, reduce your database loads with edge caching, spawn part-time databases, pool resources across accounts, and even teach your dev/test instances to sleep. Showcasing easily-applicable methods, this session could be your best invested hour all day.
Big Data Integration & Analytics Data Flows with AWS Data Pipeline (BDT207) |...Amazon Web Services
AWS offers many data services, each optimized for a specific set of structure, size, latency, and concurrency requirements. Making the best use of all specialized services has historically required custom, error-prone data transformation and transport. Now, users can use the AWS Data Pipeline service to orchestrate data flows between Amazon S3, Amazon RDS, Amazon DynamoDB, Amazon Redshift, and on-premise data stores, seamlessly and efficiently applying EC2 instances and EMR clusters to process and transform data. In this session, we demonstrate how you can use AWS Data Pipeline to coordinate your Big Data workflows, applying the optimal data storage technology to each part of your data integration architecture. Swipely's Head of Engineering shows how Swipely uses AWS Data Pipeline to build batch analytics, backfilling all their data, while using resources efficiently. Consequently, Swipely launches novel product features with less development time and less operational complexity.
Escalando una PHP App con DB sharding - PHP ConferenceMatias Paterlini
Presentación del PHP Conference Argentina 2013 sobre escalabilidad horizontal a nivel web y bases de datos para aplicaciones escritas en PHP, trabajando sobre sharding en mysql, amazon web services, y modelo de datos no relacional.
Tech Talk: RocksDB Slides by Dhruba Borthakur & Haobo Xu of FacebookThe Hive
This presentation describes the reasons why Facebook decided to build yet another key-value store, the vision and architecture of RocksDB and how it differs from other open source key-value stores. Dhruba describes some of the salient features in RocksDB that are needed for supporting embedded-storage deployments. He explains typical workloads that could be the primary use-cases for RocksDB. He also lays out the roadmap to make RocksDB the key-value store of choice for highly-multi-core processors and RAM-speed storage devices.
2nd Annual Start-up Launches with Dr. Werner Vogels (SPOT101) | AWS re:Invent...Amazon Web Services
Attend this fun, fast-paced session and see five AWS-powered start-ups launch on-stage with Amazon.com CTO, Dr. Werner Vogels. You'll hear directly from these hand-selected companies and learn how they went from an idea to launch, using the AWS cloud. This exciting hour is your firsthand look at some of the hottest new start-ups, as well as a chance to get access to their new products and features. Whether you’re a booming enterprise or a blossoming start-up, this is a re:Invent activity that’s not to be missed.
Secure Amazon EC2 Environment with AWS IAM & Resource-Based Permissions (CPN2...Amazon Web Services
Customers with multiple AWS administrators need a way to control who can do what in their Amazon EC2 environment to ensure both security and availability. This session demonstrates how to secure your Amazon EC2 environment using IAM roles and resource-based permissions.
Bringing Your Applications to the Fast Lane (CPN203) | AWS re:Invent 2013Amazon Web Services
Amazon Elastic Compute Cloud (Amazon EC2) has added a number of instance types that provide a high level of performance. Instances range from compute-optimized instances to instances that deliver thousands of IOPS. In this session, you will learn more about Amazon EC2 high performance instance types and hear from customers about how they are using these instances to improve application performance, and reduce costs.
An introduction to the different architectures of Ember and Angular, two leading JavaScript singlepage / MVC frameworks.
This presentation was given to the Los Angeles RailsBridge "Architecture" meeting on October 25, 2013.
A Modern Framework for Amazon Elastic MapReduce (BDT309) | AWS re:Invent 2013Amazon Web Services
If you've ever developed code for processing data, you know what a mess it can be—especially on Hadoop. You lack debugging tools, instant feedback, automated tests, and a sane deploy. Mortar has developed a modern framework for data processing on Hadoop and Amazon Elastic MapReduce. It is a free, open framework providing instant, step-by-step execution visibility, automated testing, reusable components, and one-button deployment. See how Mortar demonstrates this framework on Amazon EMR on a sample data set to solve a big data problem.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
2. About Magazine Luiza
Magazine Luiza is one of the largest household
appliance retail chains in Brazil. Focused on
providing durable goods for Brazil's middle and
lower-to-middle income classes.
•
•
•
•
•
731 stores
8 distribution centers
more than 23.000 workers
22.8 million customers
multi-channel strategy
Friday, November 15, 13
8. Graph Stack
Distributed Graph Database
• Used for OLTP queries
Friday, November 15, 13
Distributed database management system
9. Graph Stack
Distributed Graph Database
• Used for OLTP queries
• Native integration with Tinkerpop
Friday, November 15, 13
Distributed database management system
10. Graph Stack
Distributed Graph Database
Distributed database management system
• Used for OLTP queries
• Native integration with Tinkerpop
• Continuously available with no single point of failure
Friday, November 15, 13
11. Graph Stack
Distributed Graph Database
Distributed database management system
• Used for OLTP queries
• Native integration with Tinkerpop
• Continuously available with no single point of failure
• Elastic scalability
Friday, November 15, 13
12. Graph Stack
Distributed Graph Database
Distributed database management system
• Used for OLTP queries
• Native integration with Tinkerpop
• Continuously available with no single point of failure
• Elastic scalability
• Caching layer
Friday, November 15, 13
13. Graph Stack
Distributed Graph Database
Distributed database management system
• Used for OLTP queries
• Native integration with Tinkerpop
•
•
•
•
Friday, November 15, 13
Continuously available with no single point of failure
Elastic scalability
Caching layer
Built-in replication
14. Storing users data
Elastic
Load Balancing
EC2
instance
EC2
instance
Auto Scaling
API instances
Friday, November 15, 13
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
Cassandra cluster
15. Storing users data
Elastic
Load Balancing
EC2
instance
EC2
instance
Auto Scaling
API instances
Friday, November 15, 13
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
m2.xlarge
Cassandra cluster
39. Gremlin Graph Language
• Groovy DSL for graph traversals
• Easy to learn
Friday, November 15, 13
40. Gremlin Graph Language
• Groovy DSL for graph traversals
• Easy to learn
• Great community
Friday, November 15, 13
41. Gremlin Graph Language
• Groovy DSL for graph traversals
• Easy to learn
• Great community
• Part of the Tinkerpop stack
Friday, November 15, 13
42. Gremlin Graph Language
• Groovy DSL for graph traversals
• Easy to learn
• Great community
• Part of the Tinkerpop stack
• Works with any Blueprints enabled graph database
Friday, November 15, 13
54. Processing data with Spot Instances
Bob
dispatch a task to Amazon SQS
containing the product id
Simple Queue Service
(Amazon SQS)
Friday, November 15, 13
55. Processing data with Spot Instances
Bob
dispatch a task to Amazon SQS
containing the product id
Simple Queue Service
(Amazon SQS)
consume Amazon SQS tasks
EC2
instance
EC2
instance
m1.large
m1.large
…
Spot instances
Friday, November 15, 13
EC2
instance
m1.large
process W*A*
recommendations
56. Processing data with Spot Instances
Bob
dispatch a task to Amazon SQS
containing the product id
Simple Queue Service
(Amazon SQS)
consume Amazon SQS tasks
sync logs
sync logs
Simple Storage
Service (Amazon S3)
Friday, November 15, 13
EC2
instance
EC2
instance
m1.large
m1.large
…
Spot instances
EC2
instance
m1.large
process W*A*
recommendations
61. Personalized e-mails
Users receive e-mails when:
• A product has a price drop
• Abandoned a product on cart
• Visits many similar products
Friday, November 15, 13
63. Personalized e-mails
Bob
Bob API
notifies an
user interaction
Mailer
Manager
dispatch a task to Amazon SQS
containing the customer id
Simple Queue Service
(Amazon SQS)
m1.large
Bobby Mailer
Friday, November 15, 13
64. Personalized e-mails
Bob
Bob API
notifies an
user interaction
Mailer
Manager
dispatch a task to Amazon SQS
containing the customer id
Simple Queue Service
(Amazon SQS)
m1.large
consume Amazon SQS tasks
EC2
instance
EC2
instance
m1.large
m1.large
…
Spot instances
Bobby Mailer
Friday, November 15, 13
EC2
instance
m1.large
find the best
recommendation
for that user
65. Personalized e-mails
Bob
Bob API
notifies an
user interaction
Mailer
Manager
dispatch a task to Amazon SQS
containing the customer id
Simple Queue Service
(Amazon SQS)
m1.large
Simple Email
Service (Amazon SES)
send the e-mail
consume Amazon SQS tasks
EC2
instance
EC2
instance
m1.large
m1.large
…
Spot instances
Bobby Mailer
Friday, November 15, 13
EC2
instance
m1.large
find the best
recommendation
for that user
66. Personalized e-mails
Bob
Bob API
notifies an
user interaction
Mailer
Manager
dispatch a task to Amazon SQS
containing the customer id
Simple Queue Service
(Amazon SQS)
m1.large
sync logs
Simple Email
Service (Amazon SES)
sync logs
Simple Storage
Service (Amazon S3)
send the e-mail
consume Amazon SQS tasks
EC2
instance
EC2
instance
m1.large
m1.large
Spot instances
Bobby Mailer
Friday, November 15, 13
…
EC2
instance
m1.large
find the best
recommendation
for that user
68. Analytics with Faunus
Amazon EMR
Graph Analytics Engine
• Provides graphs input/output formats
Friday, November 15, 13
Distributed computing
69. Analytics with Faunus
Amazon EMR
Graph Analytics Engine
• Provides graphs input/output formats
and traversal language for graphs
Friday, November 15, 13
Distributed computing
70. Analytics with Faunus
Amazon EMR
Graph Analytics Engine
Distributed computing
• Provides graphs input/output formats
and traversal language for graphs
• Distributed processing of large data sets across clusters
Friday, November 15, 13
71. Analytics with Faunus
Amazon EMR
Graph Analytics Engine
Distributed computing
• Provides graphs input/output formats
and traversal language for graphs
• Distributed processing of large data sets across clusters
• Designed to scale
Friday, November 15, 13
72. Analytics with Faunus
Amazon EMR
Graph Analytics Engine
Distributed computing
• Provides graphs input/output formats
and traversal language for graphs
• Distributed processing of large data sets across clusters
• Designed to scale
• Detect and handle failures at application layer
Friday, November 15, 13
83. Metrics
• 4.3 million Magazine Luiza identified customers
• 50,000 nodes “products”
Friday, November 15, 13
84. Metrics
• 4.3 million Magazine Luiza identified customers
• 50,000 nodes “products”
• 90 million total nodes
Friday, November 15, 13
85. Metrics
•
•
•
•
4.3 million Magazine Luiza identified customers
50,000 nodes “products”
90 million total nodes
350 million total edges
Friday, November 15, 13
86. Metrics
•
•
•
•
•
4.3 million Magazine Luiza identified customers
50,000 nodes “products”
90 million total nodes
350 million total edges
700 GB of data
Friday, November 15, 13
87. Metrics
•
•
•
•
•
•
4.3 million Magazine Luiza identified customers
50,000 nodes “products”
90 million total nodes
350 million total edges
700 GB of data
Peaks with 20,000 reads/sec - Cassandra Cluster
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90. Results matter…
Solution A alone
January 2013
Friday, November 15, 13
March 2013
May 2013
July 2013
September 2013
91. Results matter…
Solution A alone
January 2013
Friday, November 15, 13
First Bob tests
March 2013
May 2013
July 2013
September 2013
92. Results matter…
Bob out for 2 weeks
Solution A alone
January 2013
Friday, November 15, 13
First Bob tests
March 2013
May 2013
July 2013
September 2013
93. Results matter…
Bob alone
Bob out for 2 weeks
Solution A alone
January 2013
Friday, November 15, 13
First Bob tests
March 2013
May 2013
July 2013
September 2013
97. Next steps
• Use Faunus to pre-process all W*A* recommendations
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98. Next steps
• Use Faunus to pre-process all W*A* recommendations
• Algorithms to identify communities in graph
Friday, November 15, 13
99. Next steps
• Use Faunus to pre-process all W*A* recommendations
• Algorithms to identify communities in graph
• Cassandra replication between regions
Friday, November 15, 13
100. Please give us your feedback on this
presentation
BDT303
As a thank you, we will select prize
winners daily for completed surveys!
Friday, November 15, 13
Thank You